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authorslaren <slarengh@gmail.com>2023-07-26 15:56:53 +0200
committerGitHub <noreply@github.com>2023-07-26 15:56:53 +0200
commit5488fb789ea5692268309baa76f67598155060be (patch)
tree0609924b82a47ce97806b9201b75ec49bdf76c31 /ggml.c
parenteb542d39324574a6778fad9ba9e34ba7a14a82a3 (diff)
ggml : allocate graphs in a context (#2392)
* ggml : graph allocation in contexts * allocate work buffer as a ggml_object in ggml_graph_compute_with_ctx * llama.cpp : allocate graph in the context * add GGML_PAD --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Diffstat (limited to 'ggml.c')
-rw-r--r--ggml.c171
1 files changed, 100 insertions, 71 deletions
diff --git a/ggml.c b/ggml.c
index 35c5615..33459f2 100644
--- a/ggml.c
+++ b/ggml.c
@@ -4071,8 +4071,8 @@ bool ggml_is_numa(void) {
////////////////////////////////////////////////////////////////////////////////
void ggml_print_object(const struct ggml_object * obj) {
- GGML_PRINT(" - ggml_object: offset = %zu, size = %zu, next = %p\n",
- obj->offs, obj->size, (const void *) obj->next);
+ GGML_PRINT(" - ggml_object: type = %d, offset = %zu, size = %zu, next = %p\n",
+ obj->type, obj->offs, obj->size, (const void *) obj->next);
}
void ggml_print_objects(const struct ggml_context * ctx) {
@@ -4212,7 +4212,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
}
size_t ggml_tensor_overhead(void) {
- return GGML_OBJECT_SIZE + GGML_TENSOR_SIZE + 16;
+ return GGML_OBJECT_SIZE + GGML_TENSOR_SIZE;
}
bool ggml_is_transposed(const struct ggml_tensor * tensor) {
@@ -4383,7 +4383,7 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
return NULL;
}
- const size_t mem_size = (params.mem_size + GGML_MEM_ALIGN - 1) & ~(GGML_MEM_ALIGN - 1);
+ const size_t mem_size = params.mem_buffer ? params.mem_size : GGML_PAD(params.mem_size, GGML_MEM_ALIGN);
*ctx = (struct ggml_context) {
/*.mem_size =*/ mem_size,
@@ -4472,12 +4472,14 @@ size_t ggml_get_max_tensor_size(const struct ggml_context * ctx) {
struct ggml_object * obj = ctx->objects_begin;
while (obj != NULL) {
- struct ggml_tensor * tensor = (struct ggml_tensor *) ((char *) ctx->mem_buffer + obj->offs);
+ if (obj->type == GGML_OBJECT_TENSOR) {
+ struct ggml_tensor * tensor = (struct ggml_tensor *) ((char *) ctx->mem_buffer + obj->offs);
- const size_t size = ggml_nbytes(tensor);
+ const size_t size = ggml_nbytes(tensor);
- if (max_size < size) {
- max_size = size;
+ if (max_size < size) {
+ max_size = size;
+ }
}
obj = obj->next;
@@ -4509,12 +4511,7 @@ static void ggml_scratch_load(struct ggml_context * ctx) {
////////////////////////////////////////////////////////////////////////////////
-static struct ggml_tensor * ggml_new_tensor_impl(
- struct ggml_context * ctx,
- enum ggml_type type,
- int n_dims,
- const int64_t* ne,
- void* data) {
+static struct ggml_object * ggml_new_object(struct ggml_context * ctx, enum ggml_object_type type, size_t size) {
// always insert objects at the end of the context's memory pool
struct ggml_object * obj_cur = ctx->objects_end;
@@ -4522,77 +4519,79 @@ static struct ggml_tensor * ggml_new_tensor_impl(
const size_t cur_size = obj_cur == NULL ? 0 : obj_cur->size;
const size_t cur_end = cur_offs + cur_size;
- size_t size_needed = 0;
-
- if (data == NULL && !ctx->no_alloc) {
- size_needed += GGML_TYPE_SIZE[type]*(ne[0]/GGML_BLCK_SIZE[type]);
- for (int i = 1; i < n_dims; i++) {
- size_needed *= ne[i];
- }
- // align to GGML_MEM_ALIGN
- size_needed = ((size_needed + GGML_MEM_ALIGN - 1)/GGML_MEM_ALIGN)*GGML_MEM_ALIGN;
- }
+ // align to GGML_MEM_ALIGN
+ size_t size_needed = GGML_PAD(size, GGML_MEM_ALIGN);
char * const mem_buffer = ctx->mem_buffer;
struct ggml_object * const obj_new = (struct ggml_object *)(mem_buffer + cur_end);
- if (ctx->scratch.data == NULL || data != NULL) {
- size_needed += GGML_TENSOR_SIZE;
+ if (cur_end + size_needed + GGML_OBJECT_SIZE > ctx->mem_size) {
+ GGML_PRINT("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n",
+ __func__, cur_end + size_needed, ctx->mem_size);
+ assert(false);
+ return NULL;
+ }
- if (cur_end + size_needed + GGML_OBJECT_SIZE > ctx->mem_size) {
- GGML_PRINT("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n",
- __func__, cur_end + size_needed + GGML_OBJECT_SIZE, ctx->mem_size);
- assert(false);
- return NULL;
- }
+ *obj_new = (struct ggml_object) {
+ .offs = cur_end + GGML_OBJECT_SIZE,
+ .size = size_needed,
+ .next = NULL,
+ .type = type,
+ };
- *obj_new = (struct ggml_object) {
- .offs = cur_end + GGML_OBJECT_SIZE,
- .size = size_needed,
- .next = NULL,
- };
+ ggml_assert_aligned(mem_buffer + obj_new->offs);
+
+ if (obj_cur != NULL) {
+ obj_cur->next = obj_new;
} else {
- if (ctx->scratch.offs + size_needed > ctx->scratch.size) {
- GGML_PRINT("%s: not enough space in the scratch memory pool (needed %zu, available %zu)\n",
- __func__, ctx->scratch.offs + size_needed, ctx->scratch.size);
- assert(false);
- return NULL;
+ // this is the first object in this context
+ ctx->objects_begin = obj_new;
+ }
+
+ ctx->objects_end = obj_new;
+
+ //printf("%s: inserted new object at %zu, size = %zu\n", __func__, cur_end, obj_new->size);
+
+ return obj_new;
+}
+
+static struct ggml_tensor * ggml_new_tensor_impl(
+ struct ggml_context * ctx,
+ enum ggml_type type,
+ int n_dims,
+ const int64_t* ne,
+ void* data) {
+
+ size_t data_size = 0;
+
+ if (data == NULL && !ctx->no_alloc) {
+ data_size += GGML_TYPE_SIZE[type]*(ne[0]/GGML_BLCK_SIZE[type]);
+ for (int i = 1; i < n_dims; i++) {
+ data_size *= ne[i];
}
+ }
- if (cur_end + GGML_TENSOR_SIZE + GGML_OBJECT_SIZE > ctx->mem_size) {
- GGML_PRINT("%s: not enough space in the context's memory pool (needed %zu, available %zu)\n",
- __func__, cur_end + GGML_TENSOR_SIZE + GGML_OBJECT_SIZE, ctx->mem_size);
+ if (ctx->scratch.data != NULL && data == NULL) {
+ // allocate tensor data in the scratch buffer
+ if (ctx->scratch.offs + data_size > ctx->scratch.size) {
+ GGML_PRINT("%s: not enough space in the scratch memory pool (needed %zu, available %zu)\n",
+ __func__, ctx->scratch.offs + data_size, ctx->scratch.size);
assert(false);
return NULL;
}
data = (char * const) ctx->scratch.data + ctx->scratch.offs;
- *obj_new = (struct ggml_object) {
- .offs = cur_end + GGML_OBJECT_SIZE,
- .size = GGML_TENSOR_SIZE,
- .next = NULL,
- };
-
- //printf("scratch offs = %zu, size_needed = %zu\n", ctx->scratch.offs, size_needed);
+ ctx->scratch.offs += data_size;
- ctx->scratch.offs += size_needed;
+ data_size = 0;
}
- if (obj_cur != NULL) {
- obj_cur->next = obj_new;
- } else {
- // this is the first object in this context
- ctx->objects_begin = obj_new;
- }
-
- ctx->objects_end = obj_new;
-
- //printf("%s: inserted new object at %zu, size = %zu\n", __func__, cur_end, obj_new->size);
+ struct ggml_object * const obj_new = ggml_new_object(ctx, GGML_OBJECT_TENSOR, GGML_TENSOR_SIZE + data_size);
- struct ggml_tensor * const result = (struct ggml_tensor *)(mem_buffer + obj_new->offs);
+ // TODO: for recoverable errors, we would need to free the data allocated from the scratch buffer here
- ggml_assert_aligned(result);
+ struct ggml_tensor * const result = (struct ggml_tensor *)((char *)ctx->mem_buffer + obj_new->offs);
*result = (struct ggml_tensor) {
/*.type =*/ type,
@@ -5026,9 +5025,11 @@ struct ggml_tensor * ggml_get_tensor(struct ggml_context * ctx, const char * nam
char * const mem_buffer = ctx->mem_buffer;
while (obj != NULL) {
- struct ggml_tensor * cur = (struct ggml_tensor *)(mem_buffer + obj->offs);
- if (strcmp(cur->name, name) == 0) {
- return cur;
+ if (obj->type == GGML_OBJECT_TENSOR) {
+ struct ggml_tensor * cur = (struct ggml_tensor *)(mem_buffer + obj->offs);
+ if (strcmp(cur->name, name) == 0) {
+ return cur;
+ }
}
obj = obj->next;
@@ -15829,6 +15830,35 @@ struct ggml_cgraph ggml_build_backward(struct ggml_context * ctx, struct ggml_cg
return result;
}
+struct ggml_cgraph * ggml_new_graph(struct ggml_context * ctx) {
+ struct ggml_object * obj = ggml_new_object(ctx, GGML_OBJECT_GRAPH, GGML_GRAPH_SIZE);
+ struct ggml_cgraph * cgraph = (struct ggml_cgraph *) ((char *) ctx->mem_buffer + obj->offs);
+
+ *cgraph = (struct ggml_cgraph) {
+ /*.n_nodes =*/ 0,
+ /*.n_leafs =*/ 0,
+ /*.nodes =*/ { NULL },
+ /*.grads =*/ { NULL },
+ /*.leafs =*/ { NULL },
+ /*.hash_table =*/ { NULL },
+ /*.perf_runs =*/ 0,
+ /*.perf_cycles =*/ 0,
+ /*.perf_time_us =*/ 0,
+ };
+
+ return cgraph;
+}
+
+struct ggml_cgraph * ggml_build_forward_ctx(struct ggml_context * ctx, struct ggml_tensor * tensor) {
+ struct ggml_cgraph * cgraph = ggml_new_graph(ctx);
+ ggml_build_forward_impl(cgraph, tensor, false);
+ return cgraph;
+}
+
+size_t ggml_graph_overhead(void) {
+ return GGML_OBJECT_SIZE + GGML_PAD(GGML_GRAPH_SIZE, GGML_MEM_ALIGN);
+}
+
//
// thread data
//
@@ -16544,10 +16574,9 @@ void ggml_graph_reset(struct ggml_cgraph * cgraph) {
void ggml_graph_compute_with_ctx(struct ggml_context * ctx, struct ggml_cgraph * cgraph, int n_threads) {
struct ggml_cplan cplan = ggml_graph_plan(cgraph, n_threads);
- struct ggml_tensor * buf = ggml_new_tensor_1d(ctx, GGML_TYPE_I8, cplan.work_size);
- GGML_ASSERT(buf);
+ struct ggml_object * obj = ggml_new_object(ctx, GGML_OBJECT_WORK_BUFFER, cplan.work_size);
- cplan.work_data = buf->data;
+ cplan.work_data = (uint8_t *)ctx->mem_buffer + obj->offs;
ggml_graph_compute(cgraph, &cplan);
}